Deriving a Probability Generating Function for Independent Poisson Variables

In summary, the conversation discusses the derivation of a Probability Generating Function for a Poisson Distribution with two independent variables, X and Y. The formula for a single variate Poisson Distribution is presented, and the question is raised whether the formula for two variables is G(t) = e^{-(\lambda_X + \lambda_Y)(1-t)}. It is confirmed that this formula is correct according to the Encyclopedia of Mathematics. The person asking the question clarifies that they are preparing for a test, not doing homework, and asks for suggestions on where to post similar problems. The conversation ends with a helpful resource being provided.
  • #1
user366312
Gold Member
89
3
Can anyone kindly tell me how I can derive a Probability Generating Function of Poisson Distribution for ##X+Y## where ##X## and ##Y## are independent?

I know that PGF for a single variate Poisson Distribution is: ##G(t) = e^{-\lambda (1-t)}##.

Then how can I derive a PGF for the same?

Is it: ##G(t) = e^{-(\lambda_X + \lambda_Y)(1-t)}## ?

Why or why not?
 
Last edited:
Physics news on Phys.org
  • #2
Encyclopedia of Mathematics describes Poisson distribution characteristics according to which you are right.
 
  • #5
user366312 said:
I am not doing homework. I am preparing for a test. I believe there are differences between these two.
Forum rules do not view it that way
 
  • Like
Likes Dale
  • #6
StoneTemplePython said:
Forum rules do not view it that way

Okay. I accept.
 
  • #7
StoneTemplePython said:
Forum rules do not view it that way

Where can/should I post these kinds of problems?
 
  • #9
user366312 said:
I am not doing homework. I am preparing for a test. I believe there are differences between these two.
user366312 said:
Okay. I accept.
Thank you. You will get great help in the schoolwork forums on your questions, as long as you show your efforts. :smile:
 

1. What is PGF for Poisson Distribution?

PGF, or Probability Generating Function, is a mathematical tool used to describe the probability distribution of a discrete random variable. In the case of Poisson Distribution, the PGF is used to calculate the probability of a certain number of events occurring in a given time period.

2. How is PGF for Poisson Distribution calculated?

The PGF for Poisson Distribution is calculated using the formula: P(x) = e^(-λ) * (λ^x) / x!, where λ is the mean number of events occurring in a given time period and x is the number of events. This formula can also be written as P(x) = e^(-λ) * λ^x * 1/x!.

3. What is the significance of PGF for Poisson Distribution in scientific research?

PGF for Poisson Distribution is commonly used in scientific research to model and analyze data that follows a Poisson Distribution. This distribution is often observed in natural phenomena such as the number of mutations in a DNA sequence or the number of particles emitted from a radioactive source. PGF allows scientists to make predictions and draw conclusions about these phenomena based on the probability of certain events occurring.

4. Can PGF for Poisson Distribution be used for continuous data?

No, PGF is specifically designed for discrete data. For continuous data, other probability distribution functions such as the normal distribution are used.

5. Are there any limitations to using PGF for Poisson Distribution?

One limitation of using PGF for Poisson Distribution is that it assumes that the events being studied are independent of each other. This may not always be the case in real-world scenarios. Additionally, PGF may not accurately model data with a large number of rare events, as the Poisson Distribution assumes a low probability of events occurring.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
14
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
12
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
846
  • Calculus and Beyond Homework Help
Replies
5
Views
221
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
986
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
5
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
Back
Top